Navigating through available music libraries is becoming more and more difficult due to the fact that the amount of easily accessible data has increased significantly over the last few years. An interdisciplinary field of research called Music Information Retrieval (MIR) investigates solutions to structure and classify musical data, to help users exploring their media. For example, it is desirable that MIR based methods are capable of classifying music in order to propose similar types of music. MIR techniques may be based on a mid-level time-frequency representation called chromagram, which specifies the energy distribution of semitones over time. The chromagram of an audio signal may be used to identify harmonic information (e.g. information about the melody and/or information about the chords) of the audio signal. However, the determination of a chromagram is typically linked to significant computational complexity.
The present document addresses the complexity issue of chromagram computation methods and describes methods and systems for chromagram computation at reduced computational complexity. In particular, methods and systems for the efficient computation of perceptually motivated chromagrams are described.